Rheumatology and Clinical Immunology, University Medical Centre Utrecht, The Netherlands.
Scand J Rheumatol. 2012 Mar;41(2):141-9. doi: 10.3109/03009742.2011.617311. Epub 2011 Dec 16.
To evaluate to what extent radiographic features of knees and hips that are normally related to osteoarthritis (OA) represent characteristics of an individual in addition to OA severity.
We studied a cohort of individuals (n = 1002) with very early signs of hip and knee OA, from the Cohort Hip and Cohort Knee (CHECK) study. Baseline radiographs were evaluated by digital analyses, using Holy's and Knee Images Digital Analysis (KIDA) software, providing distinct quantitative measures of radiographic OA features. In addition, conventional Kellgren and Lawrence (KL) grading was performed. Digital parameters were evaluated for correlations within participants between contralateral (left vs. right hip and left vs. right knee), ipsilateral (e.g. left hip vs. left knee), and diagonal joints (e.g. left hip vs. right knee). Analyses were performed separately for participants with KL grade 0-I and those with evident radiographic OA (KL grade II-III). Regression analyses determined whether demographic characteristics were related to radiographic features.
Correlations between digital parameters and KL grade were moderate, and within each KL grade large variation was found. Within participants strong correlations were found for digital parameters between joints in individuals with KL grade 0-I (R = 0.60-0.89), strongest for contralateral comparison, but no statistically significant correlations were found for participants with KL grade II-III. The demographic characteristics age, gender, height, and weight were, to a limited extent (R(2) = 0.01-0.20) but statistically significant, related to radiographic characteristics.
Using digital analyses of radiographic OA, strong correlations between joints within participants were found. These correlations diminished when OA became evident. This has implications for monitoring joint damage in (very) early OA with digital analyses.
评估膝关节和髋关节的影像学特征在多大程度上除了与骨关节炎（OA）严重程度相关之外，还代表个体的特征。
我们研究了来自髋关节和膝关节队列研究（CHECK）的队列中具有髋关节和膝关节早期 OA 迹象的 1002 名个体。使用 Holy's 和 Knee Images Digital Analysis（KIDA）软件对基线 X 光片进行数字分析，提供了明确的定量测量放射学 OA 特征的方法。此外，还进行了传统的 Kellgren 和 Lawrence（KL）分级。在参与者之间评估了数字参数在对侧（左与右髋和左与右膝）、同侧（例如左髋与左膝）和对角关节（例如左髋与右膝）之间的相关性。分别对 KL 分级 0-I 组和明显放射学 OA（KL 分级 II-III）组的参与者进行分析。回归分析确定了人口统计学特征与放射学特征之间的关系。
数字参数与 KL 分级之间的相关性为中度，并且在每个 KL 分级内都发现了很大的变化。在 KL 分级 0-I 的个体中，数字参数之间在关节之间存在很强的相关性（R=0.60-0.89），对侧比较最强，但在 KL 分级 II-III 的个体中没有发现统计学上显著的相关性。人口统计学特征（年龄、性别、身高和体重）在一定程度上（R(2)=0.01-0.20）但具有统计学意义与放射学特征相关。
使用放射学 OA 的数字分析，在参与者内部关节之间发现了很强的相关性。当 OA 变得明显时，这些相关性减弱。这对使用数字分析监测（非常）早期 OA 中的关节损伤具有影响。
